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---
license: cc-by-nc-4.0
library_name: transformers
tags:
- llama-3
model-index:
- name: badger-l3-instruct-32k
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 63.65
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 81.4
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 67.13
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 55.02
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 77.35
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 72.4
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=maldv/badger-l3-instruct-32k
name: Open LLM Leaderboard
---
*updated with fixed tokenizer config*
# Badger/δ Llama 3 Instruct 32k
I haven't been releasing my base merges so far, but this one seems worthy.
Badger is a *recursive maximally disjoint pairwise normalized fourier interpolation* of the following models:
```python
models = [
'Einstein-v6.1-Llama3-8B',
'L3-TheSpice-8b-v0.8.3',
'dolphin-2.9-llama3-8b',
'Configurable-Hermes-2-Pro-Llama-3-8B',
'MAmmoTH2-8B-Plus',
'Pantheon-RP-1.0-8b-Llama-3',
'Tiamat-8b-1.2-Llama-3-DPO',
'Buzz-8b-Large-v0.5',
'Kei_Llama3_8B',
'Llama-3-Lumimaid-8B-v0.1',
'llama-3-cat-8b-instruct-pytorch',
'Llama-3SOME-8B-v1',
'Roleplay-Llama-3-8B',
'Llama-3-LewdPlay-8B-evo',
'opus-v1.2-llama-3-8b-instruct-run3.5-epoch2.5',
'meta-llama-3-8b-instruct-hf-ortho-baukit-5fail-3000total-bf16',
'Poppy_Porpoise-0.72-L3-8B',
'Llama-3-8B-Instruct-norefusal',
'Meta-Llama-3-8B-Instruct-DPO',
'badger',
'Llama-3-Refueled',
'Llama-3-8B-Instruct-DPO-v0.4',
'Llama-3-8B-Instruct-Gradient-1048k',
'Mahou-1.0-llama3-8B',
'Llama-3-SauerkrautLM-8b-Instruct',
'Llama-3-Soliloquy-8B-v2'
]
```
I have included the notebook code I used to generate the model, for any that are curious. I have adjusted the config for rope scale 4, and 16k-32k context both seem coherent.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_maldv__badger-l3-instruct-32k)
| Metric |Value|
|---------------------------------|----:|
|Avg. |69.49|
|AI2 Reasoning Challenge (25-Shot)|63.65|
|HellaSwag (10-Shot) |81.40|
|MMLU (5-Shot) |67.13|
|TruthfulQA (0-shot) |55.02|
|Winogrande (5-shot) |77.35|
|GSM8k (5-shot) |72.40|
|